Cortex segmentation - a fast variational geometric approach

Author

Goldenberg, Roman ; Kimmel, Ron ; Rivlin, Ehud ; Rudzsky, Michael

Author_Institution

Dept. of Comput. Sci., Technion-Israel Inst. of Technol., Haifa, Israel

fYear

2001

fDate

2001

Firstpage

127

Lastpage

133

Abstract

An automatic cortical gray matter segmentation from three-dimensional brain images (MR or CT) is a well known problem in medical image processing. We formulate it as a geometric variational problem for propagation of two coupled bounding surfaces. An efficient numerical scheme is used to implement the geodesic active surface model. Experimental results of cortex segmentation on real three-dimensional MR data are provided

Keywords

biomedical MRI; brain; computational geometry; computerised tomography; differential geometry; image segmentation; medical image processing; variational techniques; CT images; MR images; automatic segmentation; cortex segmentation; cortical gray matter; coupled bounding surfaces; geodesic active surface model; geometric variational problem; medical image processing; three-dimensional MR data; three-dimensional brain images; Biomedical image processing; Brain modeling; Cerebral cortex; Cities and towns; Computed tomography; Computer science; Deformable models; Image segmentation; Solid modeling; World Wide Web;

fLanguage

English

Publisher

ieee

Conference_Titel

Variational and Level Set Methods in Computer Vision, 2001. Proceedings. IEEE Workshop on

Conference_Location

Vancouver, BC

Print_ISBN

0-7695-1278-X

Type

conf

DOI

10.1109/VLSM.2001.938891

Filename

938891